Improved functional overview of protein complexes using inferred epistatic relationships

Hdl Handle:
http://hdl.handle.net/10147/134163
Title:
Improved functional overview of protein complexes using inferred epistatic relationships
Authors:
Ryan, Colm; Greene, Derek; Guenole, Aude; van Attikum, Haico; Krogan, Nevan J; Cunningham, Padraig; Cagney, Gerard
Citation:
BMC Systems Biology. 2011 May 23;5(1):80
Issue Date:
23-May-2011
URI:
http://hdl.handle.net/10147/134163
Abstract:
Abstract Background Epistatic Miniarray Profiling(E-MAP) quantifies the net effect on growth rate of disrupting pairs of genes, often producing phenotypes that may be more (negative epistasis) or less (positive epistasis) severe than the phenotype predicted based on single gene disruptions. Epistatic interactions are important for understanding cell biology because they define relationships between individual genes, and between sets of genes involved in biochemical pathways and protein complexes. Each E-MAP screen quantifies the interactions between a logically selected subset of genes (e.g. genes whose products share a common function). Interactions that occur between genes involved in different cellular processes are not as frequently measured, yet these interactions are important for providing an overview of cellular organization. Results We introduce a method for combining overlapping E-MAP screens and inferring new interactions between them. We use this method to infer with high confidence 2,240 new strongly epistatic interactions and 34,469 weakly epistatic or neutral interactions. We show that accuracy of the predicted interactions approaches that of replicate experiments and that, like measured interactions, they are enriched for features such as shared biochemical pathways and knockout phenotypes. We constructed an expanded epistasis map for yeast cell protein complexes and show that our new interactions increase the evidence for previously proposed inter-complex connections, and predict many new links. We validated a number of these in the laboratory, including new interactions linking the SWR-C chromatin modifying complex and the nuclear transport apparatus. Conclusion Overall, our data support a modular model of yeast cell protein network organization and show how prediction methods can considerably extend the information that can be extracted from overlapping E-MAP screens.
Item Type:
Journal Article

Full metadata record

DC FieldValue Language
dc.contributor.authorRyan, Colm-
dc.contributor.authorGreene, Derek-
dc.contributor.authorGuenole, Aude-
dc.contributor.authorvan Attikum, Haico-
dc.contributor.authorKrogan, Nevan J-
dc.contributor.authorCunningham, Padraig-
dc.contributor.authorCagney, Gerard-
dc.date.accessioned2011-06-22T11:25:33Z-
dc.date.available2011-06-22T11:25:33Z-
dc.date.issued2011-05-23-
dc.identifierhttp://dx.doi.org/10.1186/1752-0509-5-80-
dc.identifier.citationBMC Systems Biology. 2011 May 23;5(1):80-
dc.identifier.urihttp://hdl.handle.net/10147/134163-
dc.description.abstractAbstract Background Epistatic Miniarray Profiling(E-MAP) quantifies the net effect on growth rate of disrupting pairs of genes, often producing phenotypes that may be more (negative epistasis) or less (positive epistasis) severe than the phenotype predicted based on single gene disruptions. Epistatic interactions are important for understanding cell biology because they define relationships between individual genes, and between sets of genes involved in biochemical pathways and protein complexes. Each E-MAP screen quantifies the interactions between a logically selected subset of genes (e.g. genes whose products share a common function). Interactions that occur between genes involved in different cellular processes are not as frequently measured, yet these interactions are important for providing an overview of cellular organization. Results We introduce a method for combining overlapping E-MAP screens and inferring new interactions between them. We use this method to infer with high confidence 2,240 new strongly epistatic interactions and 34,469 weakly epistatic or neutral interactions. We show that accuracy of the predicted interactions approaches that of replicate experiments and that, like measured interactions, they are enriched for features such as shared biochemical pathways and knockout phenotypes. We constructed an expanded epistasis map for yeast cell protein complexes and show that our new interactions increase the evidence for previously proposed inter-complex connections, and predict many new links. We validated a number of these in the laboratory, including new interactions linking the SWR-C chromatin modifying complex and the nuclear transport apparatus. Conclusion Overall, our data support a modular model of yeast cell protein network organization and show how prediction methods can considerably extend the information that can be extracted from overlapping E-MAP screens.-
dc.titleImproved functional overview of protein complexes using inferred epistatic relationships-
dc.typeJournal Article-
dc.language.rfc3066en-
dc.rights.holderRyan et al.; licensee BioMed Central Ltd.-
dc.description.statusPeer Reviewed-
dc.date.updated2011-06-17T14:03:23Z-
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